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Record W4250803146 · doi:10.2523/101401-ms

Techniques Used To Monitor and Remove Strontium Sulfate Scale in UZProducing Wells

2006· article· en· W4250803146 on OpenAlexaff
Hassouneh Al-Matar, Jamal Al-Ashhab, Shahril Mohd Mokhtar

Bibliographic record

VenueProceedings of Abu Dhabi International Petroleum Exhibition and Conference · 2006
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsSchlumberger (Canada)
FundersAbu Dhabi National Oil Company
KeywordsAbu dhabiExhibitionCitationScale (ratio)EngineeringComputer scienceMining engineeringOperations researchLibrary scienceArchaeologyGeographyCartography

Abstract

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Techniques Used To Monitor and Remove Strontium Sulfate Scale in UZ Producing Wells Hassouneh Al-Matar; Hassouneh Al-Matar Search for other works by this author on: This Site Google Scholar Jamal Kamel Al-Ashhab; Jamal Kamel Al-Ashhab Zakum Development Co. Search for other works by this author on: This Site Google Scholar Shahril Ridzauddin Mohd Mokhtar Shahril Ridzauddin Mohd Mokhtar Dowell Schlumberger Search for other works by this author on: This Site Google Scholar Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, November 2006. Paper Number: SPE-101401-MS https://doi.org/10.2118/101401-MS Published: November 05 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Al-Matar, Hassouneh, Al-Ashhab, Jamal Kamel, and Shahril Ridzauddin Mohd Mokhtar. "Techniques Used To Monitor and Remove Strontium Sulfate Scale in UZ Producing Wells." Paper presented at the Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, UAE, November 2006. doi: https://doi.org/10.2118/101401-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)Abu Dhabi International Petroleum Exhibition and Conference Search Advanced Search AbstractScale deposition in completion strings is becoming a threatening problem to produce and safely operate wells completed in the Upper ZAKUM (UZ) oil field. Calcite or Calcium Carbonate (CaCO3) scale mostly found in the upper part of the production string, and Celestite or Strontium Sulphate (SrSO4) mostly found in the lower part of the production string, are the common type of scales encounteredin Upper ZAKUM producing wells. Injection seawater (rich in Sulphate) and formation water (rich in Strontium ions) mix in the reservoir and/or wellbore under varying conditions resulting into Strontium Sulfate Scale formation in downhole equipment. While CaCO3 scales are possible to be removed by the use of common acids and wireline tools, Strontium Sulphate scale requires special techniques to remove chemically and/or mechanically, and present the most challenges to achieve complete removal.This work will describe ZADCO scale management strategy to monitor and remove Strontium Sulfate scale in Upper Zakum producing wells. A scale prediction simulator is used to identify wells with high scaling risk. Scale Risk Matrix (SRM) is being developed to classify the scale risk in each well. The Chlorides content, the percentage sea water in the produced water, the production rate, the percentage water cut and scaling index are the main parameters that are used to calculate the overall scaling risk for a certain string. The wells classified as high scaling risk wells, are included on a monitoring list for periodical scale checks by running gauge cutters on slickline. Scale samples are collected and sent to the lab for analysis and scale type identification.The category of strings with a scale thickness less than 0.25″ are treated with a chemical scale dissolver, the wells containing scale thicker than 0.25″ are treated with downhole cleaning tools run on Coiled Tubing.In 2005, ten wells severely scaled with Strontium Sulphate were mechanically treated using Coiled Tubing, Mills and motor, high pressure rotating tool with Sterling Beads* and Polymer as the cleaning fluid. Most of the job objectives were not completely accomplished due to severe hard scaling conditions.IntroductionUpper Zakum field (4th largest known field in the world), operated by ZADCO, and located offshore Abu Dhabi. The field was discovered in early sixties. Oil production started in 1982.Seawater injection to support the reservoir pressure started in 1984. Water breakthrough started in 1990. Strontium Sulfate (SrSO4) scale was observed in 1991. Since 1991 there has been an increase in scale related problems such as interference with producing wells wireline operation and minor production losses.With more than 400 producers and more than 350 pressure support water injectors in UZ, a solid Well Integrity Management System (WIMS)1 was put in place by ZADCO that helps to identify, prevent and solve all the problems related to lack of integrity in each well.Scale management system is a major part of ZADCO WIMS. In 2001 ZADCO carried out a scale study to evaluate the scale risk in UZ field. It was found that the the maximum Scaling Index (SI) (need to explain what is scale index) for mixtures of UZ formation water and injected seawater at reservoir conditions is 0.57 for strontium sulfate which is only just above the positive threshold SI of +0.40 for the lowest zone of scale risk to the production problems. This would tend to indicate that UZ field would not have significant production declines due to scale. Keywords: Hydrate Remediation, wax remediation, scale remediation, paraffin remediation, wax inhibition, hydrate inhibition, asphaltene inhibition, dissolver, production string, management system Subjects: Production Chemistry, Metallurgy and Biology, Inhibition and remediation of hydrates, scale, paraffin / wax and asphaltene This content is only available via PDF. 2006. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.240
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations6
Published2006
Admission routes1
Has abstractyes

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